MétaCan
Menu
Back to cohort

Clinical Performance of the BD Respiratory Viral Panel for BD MAX™ System in Detecting SARS-CoV-2, Influenza A and B, and Respiratory Syncytial Virus

2024· article· en· W4401361291 on OpenAlexaff
Sonia Paradis, Barbara Van Der Pol, Nicolette Athanasiou Kaatz, Thomas E. Davis, Nathan A. Ledeboer, Matthew L. Faron, William Laviers, Elizabeth Lockamy, Karen Yanson

Bibliographic record

VenueDiagnostic Microbiology and Infectious Disease · 2024
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsBecton Dickinson (Canada)
FundersBiomedical Advanced Research and Development AuthorityBDU.S. Department of Health and Human ServicesAdministration for Strategic Preparedness and Response
KeywordsRespiratory systemClearanceMedicineVirologyVirusRetrospective cohort studySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Influenzavirus BInfluenza A virusOrthomyxoviridaeCoronavirus disease 2019 (COVID-19)Internal medicine

Abstract

fetched live from OpenAlex

Using a nasopharyngeal (NP) or anterior nasal (NS) swab from prospectively collected or retrospective specimens, we assessed the clinical performance of the BD Respiratory Viral Panel (BD RVP) for BD MAX System against FDA-cleared or authorized comparators. Across prospective and retrospective specimens, positive percent agreement (PPA) was ≥ 98.4% for SARS-CoV-2, ≥ 96.7% for influenza (flu) A, ≥ 91.7% for respiratory syncytial virus (RSV), and 100% for flu B (retrospective only) while negative percent agreement (NPA) was ≥ 97.7% across all targets, leading to the assay FDA clearance. A head-to-head comparison of NS versus NP results with BD RVP was also performed; PPA was ≥ 90% and NPA ≥ 98.2% for SARS-CoV-2, flu A and RSV. These findings confirm that the BD MAX RVP assay performs well for detection and differentiation of the three viruses in NP and NS specimens, with strong interrater agreements for NS versus NP comparisons.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.014
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.376
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueDiagnostic Microbiology and Infectious DiseaseSame topicRespiratory viral infections researchFrench-language works237,207